Environmental Management (2011) 47:279–290 DOI 10.1007/s00267-010-9598-8
ENVIRONMENTAL ASSESSMENT
Assessing Ecological Water Quality with Macroinvertebrates and Fish: A Case Study from a Small Mediterranean River Maria Th. Cheimonopoulou • Dimitra C. Bobori Ioannis Theocharopoulos • Maria Lazaridou
•
Received: 25 March 2009 / Accepted: 1 December 2010 / Published online: 19 December 2010 Ó Springer Science+Business Media, LLC 2010
Abstract Biological elements, such as benthic macroinvertebrates and fish, have been used in assessing the ecological quality of rivers according to the requirements of the Water Framework Directive. However, the concurrent use of multiple organism groups provides a broader perspective for such evaluations, since each biological element may respond differently to certain environmental variables. In the present study, we assessed the ecological quality of a Greek river (RM4 type), during autumn 2003 and spring 2004 at 10 sites, with benthic macroinvertebrates and fish. Hydromorphological and physicochemical parameters, habitat structure, and riparian vegetation were also considered. Pollution sensitive macroinvertebrate taxa were more abundant at headwaters, which had good/ excellent water quality according to the Hellenic Evaluation System (HES). The main river reaches possessed moderate water quality, while downstream sites were mainly characterised as having bad or poor water quality, dominated by pollution-tolerant macroinvertebrate taxa. Macroinvertebrates related strongly to local stressors as chemical degradation (ordination analysis CCA) and riparian quality impairment (bivariate analysis) while fish did not. Fish were absent from the severely impacted lower
M. Th. Cheimonopoulou (&) M. Lazaridou Laboratory of Zoology, School of Biology, Aristotle University of Thessaloniki, P.O. Box 134, 541 24 Thessaloniki, Greece e-mail:
[email protected] M. Th. Cheimonopoulou D. C. Bobori Laboratory of Ichthyology, School of Biology, Aristotle University of Thessaloniki, P.O. Box 134, 541 24 Thessaloniki, Greece I. Theocharopoulos 24 Filippoupoleos Street, 591 00 Veria, Imathia, Greece
river reaches. Furthermore, external pathological signs were observed in fish caught at certain sites. A combined use of both macroinvertebrates and fish in biomonitoring programs is proposed for providing a safer assessment of local and regional habitat impairment. Keywords Fish Invertebrates Physicochemical parameters WFD Ecological assessment R.H.S.
Introduction The pollution, degradation, and overexploitation (Giller 2005; Navarro and others 2007) of surface inland water resources, has resulted in their inclusion among the most threatened habitats in the world. These perturbations cause, among other problems, alteration of natural hydrological regime, loss of habitats for biota, chemical pollution, the obstruction of natural connections of stream systems, and riparian degradation (Harris and Silveira 1999; Molnar and others 2002). As a consequence, the biological, physicochemical, and hydromorphological characteristics of a large number of rivers have deteriorated to such an extent that there has been a worldwide consensus for their recovery and rehabilitation (Globevnik and Kaligaric 2005; West and others 2006; Alam and others 2007). Hence, the European Commission enforced the Water Framework Directive 2000/60/EC (WFD, European Commission 2000), focusing on the establishment of a framework for the protection of all waters. Ecological status of surface waters is assessed by hydromorphological, biological, and physicochemical quality elements (WFD, European Commission 2000). Macroinvertebrates and fish are among the biological elements used for assessing ecological river quality since both groups have been shown to respond to
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habitat variability and water chemistry on various scales (Infante and others 2009), making them a useful diagnostic and regulatory tool (Karr 1981). In particular, benthic macroinvertebrates are considered as good indicators of local scale conditions (Metcalfe 1989; Freund and Petty 2007), constituting the largest database for biomonitoring running waters in Europe (Buffagni and others 2005). Fish assemblages are also considered as sensitive indicators of habitat quality in rivers (Ormerod 2003), fulfilling a fundamental role in assessing habitat degradation (West and others 2006) and river connectivity (Schmutz and Jungwirth 1999; Schiemer 2000) on a regional scale. However, both groups have been shown to be impacted by human activities on a large scale (e.g., landscape futures, topography) that indirectly affect factors that influence biota on a local scale (e.g., water quality, physical habitat) (Allan 2004; Infante and others 2009). In biomonitoring programs, biological elements can be used either singly or jointly, in assessing the ecological status of river ecosystems according to the WFD. However, the concurrent use of multiple organism groups provides a broader perspective in assessing ecological water quality, as each biological element may respond differently to certain environmental variables (Townsend and others 2003; Berkman and others 2005; Johnson and others 2006; Freund and Petty 2007). As a member of the European Union, Greece must fulfill all the requirements of the EU WFD and provide data on the ecological status of its surface waters. However, no national system for the assessment of the ecological quality of running waters using biological elements exists in this country. Studies already conducted have mainly been based on benthic macroinvertebrates and their response to abiotic parameters (hydromorphological, and/or physicochemical) (Kampa and others 2000; Lazaridou-Dimitriadou and others 2000, 2004; Argyroudi and others 2008). Based on these results, the Hellenic Evaluation System (HES) for Northern and Central Greece was developed (Artemiadou and Lazaridou 2005) and intercalibrated (Artemiadou and others 2008) for small/medium (catchment area 10–1000 km2) Mediterranean mountainous rivers (RM4 type) (Van de Bund and others 2004). In contrast, no national fish-based evaluation system for the assessment of ecological river quality exists in the country. However, a multi-metric fish index for the assessment of the ecological status of mountainous streams and rivers has recently been proposed by Economou and others (2007), but it has not yet been intercalibrated. Lastly, very few studies that use two or more biological elements as bio-indicators for assessing the ecological status of Greek rivers exist (IliopoulouGeorgoudaki and others 2003; Lazaridou-Dimitriadou and others 2004).
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This study aims to assess the ecological quality of a small Mediterranean river (RM4 type), using hydromorphological and physicochemical parameters, macroinvertebrates, and fish. Additional objectives include assessing the response of each biological element to different stressors (pollution, hydromorphological alterations, habitat degradation), thus to evaluate the concordance between the two biological elements and to contribute in the future to the development of a multi-biotic index.
Materials and Methods Study Area The Tripotamos river (catchment area 212 km2) is a tributary of the Aliakmon river (catchment area 8700 km2), which flows into the N. Aegean Sea (Fig. 1). Water, benthic macroinvertebrates, and fish were sampled at 10 sites during autumn 2003 (September) and spring 2004 (April). Four sites were located near springs (Mavroneri tributary: sites 1, 3; Asproneri tributary: site 5; Lianovrochi tributary: site 7) and six along the main river course (sites 2, 4, 6, 8, 9, 10) (Fig. 1). Site wet distance from the Tripotamos confluence point into the Aliakmon river is expressed in kilometers. Site selection was based on land use and anthropogenic impacts (Corine land cover; Center of Hydrological Information 2005 and visual estimation within 50 m of banktop along 500 m upstream each site). Due consideration was also given to ease of access. Sites were subjected to non-point (agricultural runoff: sites 2, 4,
Fig. 1 Map of the study area with the sampling sites. Land use, major springs, point sources of pollution, villages, and urban areas are also mentioned
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9, 10) and/or point (municipal sewage and wastes: sites 2, 4, 6, 8, 9) sources of pollution (based on published technical reports and/or information gathered by local authorities) or water abstraction (2, 5, and 7) (Fig. 1). Physicochemical and Hydrological Parameters— Habitat Characteristics Dissolved oxygen (D.O. in mg/l and %), pH, water and air temperature (Wtemp and Atemp, °C), conductivity (lS/ cm), turbidity (NTU), and altitude (m) were measured in situ at each sampling site (using an oxygen meter, E.O.T. 200 WTW; a pH meter, 323/SET1 WTW; a conductivity meter, WTW LS 196; a turbidimeter, DRT-ISCE Scientific inc; a GPS unit, Magellan 315). Biochemical oxygen demand (B.O.D.5 mg/l), nutrients (NO3-N, NO2-N, NH4-N, and PO4-P, mg/l), hardness (CaCO3, mg/l), and total suspended solids (TSS, mg/l) were determined according to APHA (1985). Collections of water samples, as well as in situ measurements of physicochemical parameters were made at the subsurface of the mid-channel. Wet river width (m) was measured. Flow and water depth were measured at 10 equidistant points (or less when river width \2 m) at a channel cross-section. Flow was estimated using a flow meter (type Swoffer 2100) at fourtenths of the water depth above the stream bed. Water discharge (m3/sec), average flow (m/sec), and maximum and mean depth (m) were then calculated. The coverage percentage, of the riparian zone (at the edge between the water channel and the banks) and its canopy over the water surface, aquatic vegetation, and substrate composition were estimated visually. Substrate composition was assessed using the Wentworth scale (Wentworth 1922) but approximated in 3 categories: coarse when the sum of boulders, cobbles, pebbles, and gravel [70%; category 1, fine when sand and silt [70%; category 2, and in cases where the composition was variant and could not be classified as coarse or fine, the site was classified as category 3. Habitat Quality The River Habitat Survey (RHS) (Raven and others 1998) was used for river habitat assessment and physical character by visual observations of substrate, flow types, land use in the adjacent river corridor, etc. RHS data were collected by means of 10 equidistant ‘spot check’ transects of 1 m wide and a sweep-up summary of 500 m (Raven and others 1998). Artificial modifications of the channel and bank structure were expressed by the Habitat Modification Score (HMS), according to six quality classes: pristine (score:0), semi-natural (score:0–2), predominately unmodified (score:3–8), obviously modified (score:9–20), significantly modified (score:21–44), and severely modified
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(score 45 or more). Moreover, we used HMS weighted ‘penalty’ points to describe different types of physical alterations (1 for resectioning, 2 for reinforcement, etc.). Riparian quality was evaluated by the Qualitat de Bosc de Ribeira index, (QBR; Munne and others 2003) in river lengths of 100 m. This index ranges from 0 to 100 by adding the scores of four components of riparian habitat i.e. total riparian vegetation cover, vegetation cover structure and quality, and river channel alteration. Each score (ranges between 0 and 25) is the sum of positive or negative points assigned to specific habitat features (e.g., percentage of tree cover over 75% scores ?25 points, trees distributed regularly and shrub land over 50% scores -10 points), which are visually estimated. Riparian habitat quality of each site is defined according to five quality classes: riparian habitat in natural condition-excellent quality (score C95), some disturbance-good quality (score: 75–90), disturbance important-fair quality (score: 55–70), strong alteration-poor quality (score: 30–50), and extreme degradation-bad quality (score B25). Biological Elements and Ecological Quality A composite sample of benthic macroinvertebrates was collected at each site in both sampling periods (autumn 2003 and spring 2004) according to the semi-quantitative 3-min kick and sweep method (Armitage and others 1983) using a 250 9 230 mm, D-shaped pond net (surface 575 cm2, mesh size 0.9 mm, depth 27.5 cm) (ISO 7828:1985; EN27828:1994). Armitage and others (1983) note that this method uses no precise definition of the collecting area and aims to obtain a comprehensive list of taxa with the minimum sampling effort by proportional sampling of representatives of all existing instream habitat types (macrophyte beds, woody snags, bars, natural or artificial substrates at riffles, runs, and pools). The habitats were detected, within a 50 m sample reach, according to Habitat Richness Matrix (GHRM) (Chatzinikolaou and others 2006). Macroinvertebrates were preserved in 4% formaldehyde solution until sorted. Specimens were identified stereoscopically mainly to family level and abundance of each taxon was noted. The Hellenic Evaluation system assessed the river’s ecological quality. This is composed by, HES, which is the sum of macroinvertebrate family sensitivity scores per sample, its average (AHES: HES divided by the number of taxa found), and an Interpretation Index (HESII: semi-sum of HES and AHES according to rich or poor habitats) (Artemiadou and Lazaridou 2005). This system results in five quality classes (High, Good, Moderate, Poor, and Bad ecological water quality) as the WFD demands, and it has been intercalibrated for RM4 river type (Artemiadou and others 2008).
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Fish assemblage data were obtained by electrofishing (wading) according to CEN standards (CEN 2002). A pure direct current device with one hand-held anode (type Hans Grassl 200/2) was used. At each site, one sampling run was performed in a herringbone pattern in an upstream direction, within a 50 m reach (CEN 2002), covering all different habitats. Fish were identified at species level (Kottelat and Freyhof 2007) and measurements of total length (TL) (to the nearest mm) and total weight (TW) (to the nearest g) were recorded in situ, after the fish had been anaesthetized with methylpentanol. Revived fish were returned to the river, while a few individuals were preserved in formaldehyde solution (10%) for taxonomic confirmation in the laboratory.
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Spearman’s rank correlation analysis was also followed for evaluating the influence of HMS and QBR scores on fish and macroinvertebrate abundances, as well as benthic macroinvertebrate richness. Differences (a) between the two sampling periods with regard to environmental variables, macroinvertebrate and fish relative abundances and richness, and (b) between environmental variables at sites located close to springs (sites 1, 3, 5, and 7) and the mainstream (sites 2, 4, 6, 8, 9, 10), were assessed by applying the Mann-Whitney U-test (Statistica 6). Linear regression analysis (Statistica 6) was applied between HESII results and site distance from the Tripotamos river confluence point into the Aliakmon river, to quantify a longitudinal degradation trend.
Statistical Analysis Canonical correspondence analysis (CCA) quantified the relationship between macroinvertebrate communities present in each sample and significant environmental variables that best explain them (CANOCO 4; Ter Braak and Smilauer 1998). Environmental variables were standardized (water and air temperature and pH) or arcsine transformed (D.O. % and percentages of aquatic and riparian vegetation and canopy coverage) prior to CCA analysis. The rest of the environmental variables and macroinvertebrate relative abundances were log(x ? 1) transformed. The environmental variables (transformed as mentioned above) were analyzed by Principal Component Analysis (PCA) (Primer 6: Clarke and Gorley 2006) to specify the reduced set of variables explaining a percentage of the variability in the ordination of samples in space. Only components (PCs) with eigenvalues [1.0 were interpreted. The scores of the first two PCs were used for plotting samples on a 2-d PC plot. Variables with a significant correlation, higher than |0.3|, reflecting their contribution to each axes, were represented by vectors in the same plot. Linear regression analysis (Statistica 6) was applied between PC1 and PC2 scores independently and (a) fish abundances, (b) relative abundances of sensitive, moderately tolerant, and pollution tolerant macroinvertebrate families, and (c) HES, AHES, and HESII indices (logarithmically transformed), to test their response to the most important environmental variables, as summarized in PCs axes. Furthermore, a multiple regression model (Statgraphics plus 5) was used to describe differences in the explanatory power of environmental variables (PC1 and PC2 factor scores) with regard to macroinvertebrate vs. fish abundances (square root transformed). The partial regression coefficients (beta-weights) were used to assess the dependence of each variable on the fitted model (Zar 1984).
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Results Physicochemical and Hydromorphological Parameters: Habitat Characteristics Hardness, BOD5, water and air temperature (Wtemp, Atemp), dissolved oxygen (D.O.), and nutrient concentration (NH4-N, NO3-N, PO4-P) differed significantly between the two sampling periods (autumn 2003, spring 2004) (Mann-Whitney U test, P \ 0.05, df = 18), with the higher mean nutrient values having been recorded in spring (Table 1). Downstream sites (9 and 10) exhibited the highest values of TSS (57.7 and 54 mg/l respectively) in autumn sampling while during spring sampling the highest values of NO2-N (0.002 and 0.025 mg/l), NO3-N (0.90 and 0.91 mg/l), NH4-N (1.66 and 1.58 mg/l), PO4-P (0.137 and 0.057 mg/l), and B.O.D.5 (7.8 and 8.9 mg/l) were recorded at the same sites. Locally, high values of NH4-N concentrations were also observed during spring at sites 2 (0.047 mg/l), 6 (0.082 mg/l), and 8 (0.473 mg/l). Maximum values of conductivity (487 and 516 lS/cm for autumn and spring respectively), pH (8.25 and 8.19), and hardness (300 and 312 mg CaCO3/l) were measured at site 7 in both periods. Generally, sites receiving spring water located at the tributaries (1, 3, 5, and 7), exhibited lower mean values of turbidity, TSS, NO2-N, and NO3-N than the mainstream sites (2, 4, 6, 8, 9, and 10) (Mann-Whitney U test, P \ 0.05, df = 18). Substrate was characterized as coarse at all sites, except at site 3, where it presented a variant composition. Diversity of physical features in riparian and channel river corridor (e.g., shading of the river channel, extent of trees, etc.) was high at sites 1, 3, 5, 6, and 7. Habitat Modification Score (HMS) ranged from 1 (site 6) to 13 (site 5) and estimated one site (6) as semi-natural, 6 sites (1, 3, 4, 8, 9, 10) as predominantly unmodified, and three
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Table 1 Mean (±SE), minimum (min) and maximum (max) values of hydromorphological and physicochemical parameters in Tripotamos river (autumn 2003 and spring 2004) Parameters
Autumn Mean
Spring SE
Min
Max
Mean
SE
Min
Max
Mean flow (m/s)
0.41
0.079
0.02
0.79
0.52
0.076
0.17
0.79
Mean discharge (m3/s)
0.71
0.166
0.01
1.48
0.87
0.204
0.06
1.93
River width (m) Max stream depth (m)
3.9 0.37
0.559 0.053
1.4 0.09
7.3 0.58
5.0 0.37
0.608 0.038
2.2 0.15
8.0 0.54
Mean stream depth (m)
0.25
0.034
0.063
0.395
0.22
0.024
0.099
0.02
D.O. (%)
0.92
0.028
0.76
1.04
0.99
0.020
0.89
1.08
D.O. (mg/l)
9.29
0.284
7.60
10.70
10.68
0.277
9.40
11.90
pH
7.7
0.110
7.1
8.3
7.7
0.116
7.1
8.2
Twater (°C)
14.6
0.647
12.7
18.1
12.2
0.509
8.5
14.3
Tair (°C)
21.7
0.614
19.5
26.2
16.2
0.897
9.2
18.5
Conductivity (lS/cm)
413
10.711
384
487
407
12.860
368
516
Turbidity (NTU)
5.62
3.347
0.28
32.10
4.03
1.514
0.28
15.22
B.O.D.5 (mg/l)
4.49
0.378
3.30
6.90
2.69
0.955
0.80
8.90
T.S.S. (mg/l)
12.82
7.214
0.20
57.75
7.28
4.041
0.10
40.48
Hardness (CaCO3, mg/l)
239.2
7.200
216.0
300.0
230.0
9.376
208.0
312.0
MH4-M (mg/l)
0.013
0.003
0.000
0.029
0.355
0.212
0.013
1.664
MO3-M (mg/l)
0.515
0.072
0.162
0.826
0.736
0.049
0.477
0.912
MO2-M (mg/l) PO4-P (mg/l)
0.003 0.021
0.001 0.002
0.001 0.015
0.007 0.033
0.006 0.024
0.003 0.014
0.001 0.004
0.025 0.138
For all cases n = 10
sites (2, 5, 7) as obviously modified. The index of Riparian Quality (QBR) ranged from 45 (site 10) to 100 (site 3) and classified the sites in three groups that presented: (a) excellent riparian quality (site 3), (b) good riparian quality (sites:1, 5, 7), and (c) moderate riparian quality (sites:2, 4, 6, 8, 9, 10). Macroinvertebrates A total of 59,520 individuals which belonged to 65 different taxa were found. Limnephilidae (Trichoptera) and Empididae (Diptera) presented higher relative abundances in spring, while the opposite was evident for Tipulidae (Diptera) (Mann-Whitney U test, P \ 0.05, df = 18). Species richness did not differ significantly between the two seasons (Mann-Whitney U test, P [ 0.05, df = 18). When considering the sites located at the main river (Fig. 1), a dominance of pollution tolerant families is evident (57.9%) at downstream sites (8, 9, 10) compared to the upstream ones (2, 4, and 6). The opposite was true for the pollution sensitive families that dominated the upstream sites (79.3%). Relative abundances of sensitive and tolerant macroinvertebrate families as well as sensitive macroinvertebrate taxa richness correlated strongly to the QBR score (rs = 0.776, rs = -0.782, and rs = 0.842 respectively, for all cases P \ 0.05).
Eleven of the 22 environmental variables were only used in CCA analysis according to the Monte Carlo test and the inflation factor (which had to be \ 20). The first two ordination axes explained 56.4% of the variance of the species-environment relation and 42.3% of the variance of species data (Fig. 2). Axis I (eigenvalue = 0.427, F ratio = 2.752, P = 0.03) was mainly related to TSS (r = 0.90) and altitude (r = -0.62), while axis II (eigenvalue = 0.345) was mainly related to hardness (r = 0.83) and conductivity (r = 0.81) (Fig. 2). Autumn (A) and spring (S) samples of downstream sites 8, 9, and 10 were related positively to axis I as they presented the highest values of TSS, while autumn and spring samples of site 7 were strongly related to axis II, as they exhibited the highest values of hardness and conductivity (Fig. 2a). Similarly, taxa of downstream sites were ordinated on the positive side of axis I (Fig. 2b). Taxa of high altitude sites (1, 2, 3, 4, 5) were ordinated at the negative side of axis II. Fish A total of 554 individuals, belonging to two native fish species, Salmo trutta Linnaeus, 1758 (TL:3.5–37.3 cm, TW:0.49–741 g), and Barbus balcanicus Kotlı´k, Tsigenopoulos, Ra´b & Berrebi, 2002 (TL:2.1–19.3 cm, TW:0.03–87.21 g), were captured (Table 2). Fish were
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2.5
284
a
Axis II
7A
7S Conductivity
Hardness Wtemp pH PO4-P BOD5 9S NO2-N
5A 8A 2A 3A 1S 6A 5S 6S 3S 2S 8S 4A 4S
-1.5
DO
Altitude
10A 9A
1A
10S
Axis I TSS
Ecological Quality Evaluation
Discharge 3.0
4.0
-2.0
Aes
Hal Heb Pot Ple Hydro Les Perlo Cae Gom Perli Hydra
Axis II
b
Str Dix
Cap Cer Ath
-1.0
Hydrae
Dry Tip Tab
Ecn Lep Conductivity Hardness Wtemp pH Dit Vel Hydrop SimPO4-PBOD5 Ephi NO2-N ChiNR DO Elm Rhy Bae Leu TSS Cal Emp Hydro Ase Glo Hep Altitude Cur Lim Lib Lym Gam Psym Oli TaeAstSph Discharge Hydrob
ChiR
Tub Hyg Phy
Axis I
4.0
Fig. 2 CCA ordination plot of macroinvertebrate (a) samples (A autumn, S spring) and (b) families, against the hydromorphological and physicochemical parameters (eigenvalues for axis I: 0.427 and for axis II: 0.345). The length of the vectors in this plot (93 in a) reflects the significance of each variable contribution to each axis. Abbreviations for family names: Psyd Psychodidae, Tub Tubificidae, Hyg Hygrobiidae, Phy Physidae, ChiR Chironomidae Red, Dix Dixidae, Str Stratiomyidae, Hydra Hydracarina, Hal Haliplidae, Heb Hebridae, Pot Potamonidae, Aes Aeshnidae, Ple Pleidae, Hydro Hydroptilidae, Les Lestidae, Gom Gomphidae, Perlo Perlodidae, Perli Perlidae, Cae Caenidae, Cap Capniidae, Cer Ceratopogonidae, Dry Dryopidae, Athe Athericidae, Hydrae Hydraenidae, Tip Tipulidae, Tab Tabanidae, Ecn Ecnomidae, Lep Leptophlebiidae, Hydrop Hydropsychidae, Ephi Ephemeridae, Ephe Ephemerelidae, Vel Velidae, Cal Calopterygidae, Elm Elminthidae, Rhy Rhyacophilidae, Emp Empididae, Hep Heptagenidae, Ast Astacidae, Lib Libellulidae, Gam Gammaridae, Tae Taeniopterygiidae, Lim Limonidae, Psym Psychomyidae, Cur Curculionidae, Oli Oligochaeta, Sph Sphaeridae, Nem Nemouridae, Ner Neritidae, Limn Limnaephilidae, Plana Planaridae, Plano Planorbidae, Bae Baetidae, Leu Leuctridae, Ase Asellidae, Glo Glossiphonidae Lym Lymnaeidae, ChiNR Chironomidae not red, Dit Dityschidae, Anc Ancylidae, Sim Simuliidae, Cor Cordulegasteridae
totally absent at sites 1, 5, 9, and 10. Relative fish abundances did not differ significantly between the two sampling periods (Mann-Whitney U-test, P [ 0.05, df = 18).
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The interpretation index of the Hellenic evaluation system (HESII results) assessed sites 9 and 10 as disturbed (bad and poor water quality) (Table 3). Sites 1, 3, and 5 exhibited good water quality in both seasons, while site 7 presented excellent water quality in autumn and good water quality in spring. For the remaining sites (2, 4, 6, 8), water quality was evaluated as moderate in both seasons (Table 3). When the distance of each site from the confluence point of the Tripotamos into the Aliakmon river was regressed against the HESII values, a significant positive relation was found (R2 = 0.486, P \ 0.001).
Psyd
Ner Anc Nem Cor Ephe Limn Plana Plano
-2.0
No correlation was evident between fish abundances and HMS and QBR scores (P [ 0.05, df = 8). Barbus balcanicus individuals caught at site 8 presented pathological signs (skin tumours, red spots, missing parts of operculumgill cover- and caudal fin) (6% in autumn and 38% in spring). Histological examination showed only external abnormalities (skin tumours). Additionally, red spots were also observed in 16% Barbus balcanicus specimens at site 7 during spring. No pathological signs were evident in Salmo trutta.
PCA Analysis PCA analysis produced five statistically significant (eigenvalues [1.0) principal components (PCs). The first two PCs explained 51.6% of the total variance (Fig. 3). PC1 correlated positively to NO2-N (r = 0.368), NH4-N (r = 0.342), PO4-P (r = 0.341), and TSS (r = 0.338), and negatively to altitude (r = -0.344). PC2 correlated negatively to conductivity (r = -0.477) and hardness (r = -0.438). Low altitude sites with high TSS and nutrients (9 and 10) were ordinated on the positive side of PC1, while sites 1 and 5 with high altitude, were ordinated on its negative side. These sites were fishless. The rest of the high altitudelow nutrient-low TSS sites (2, 3, 4) were positioned on the negative side of PC1. These sites were occupied by Salmo trutta. Conductivity and hardness correlated negatively to PC2 separating site 7 (Fig. 3) from the rest sites. This site presented the highest Barbus balcanicus abundance. The three macroinvertebrate indices (HES, AHES, HESII) correlated negatively only to PC1 scores (R2 = 0.414, R2 = 0.469, and R2 = 0.469 respectively; P \ 0.005). Furthermore, when the relative abundances of sensitive, moderately tolerant, and pollution tolerant benthic macroinvertebrate families were considered, a negative correlation was extracted between PC1 scores and the sensitive ones (R2 = 0.414, P \ 0.001) and a positive one with the tolerant ones (R2 = 0.271, P \ 0.02). Relative abundances
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Table 2 Fish species sampled at each sampling site Species name
Barbus balcanicus
Salmo trutta
Sites
6S
7A
7S
8A
8S
2A
2S
3A
3S
4A
4S
8S
Abundance (ind./100 m2)
2
196
101
36
30
4
16
1
2
4
4
0.3
TL (cm)
6.49 ± 0.19 (2.10–19.30)
TW (g)
4.88 ± 0.35 (0.025–87.21)
44.07 ± 8.37 (0.49–741)
n
496
58
11.99 ± 1.09 (3.50–37.30)
Numbers denote the sites, A autumn, S spring. Abundance is expressed as individuals per 100 m2 sampled area. Total length (TL, cm) and total weight (TW, g) refer to the means (±SE). Minimum and maximum values are noted in parenthesis (n = number of individuals caught in total) 4
Table 3 Hellenic evaluation score (HES), its average (AHES), their interpretation index (HESII), and habitat quality HES
AHES
Habitat quality
HESII
HESII interpretation
1A
1305
59.32
Rich
3.5
Good
1S
1367
59.44
Rich
4
Good
2A
1100
52.38
Rich
3
Moderate
2S
1168
50.78
Rich
3
Moderate
3A
1048
58.22
Rich
3.5
Good
3S
1238
58.95
Rich
3.5
Good
4A
1114
53.05
Rich
3
Moderate
4S
1108
52.76
Rich
3
Moderate
5A
1257
62.85
Rich
3.5
Good
5S
1127
59.32
Rich
3.5
Good
6A 6S
782 1040
48.88 52.00
Rich Rich
2.5 3
Moderate Moderate
7A
2071
59.17
Rich
4.5
Excellent
7S
1086
63.88
Rich
3.5
Good
8A
1213
50.54
Rich
3
Moderate
8S
1066
46.35
Rich
3
Moderate
9A
284
31.56
Rich
1
Bad
9S
529
44.08
Rich
2
Poor
10A
364
33.09
Rich
2
Poor
10S
652
43.47
Rich
2
Poor
The scaling of the water quality interpretations is: [4 = excellent, 3.1–4 = good, 2.1–3 = moderate, 1.1–2 = poor, 0–1 = bad water quality (sample abbreviations, S spring, A autumn)
of moderately tolerant and pollution tolerant families further correlated to the PC2 component (R2 = 0.269 and R2 = 0.210 respectively, P \ 0.05). No relationship was evident between fish species abundances and the PC1 scores (P [ 0.05). In contrast, abundances of both fish species were correlated significantly (P \ 0.05) to PC2 scores (Salmo trutta: R2 = 0.243, positive correlation; Barbus balcanicus: R2 = 0.215, negative correlation). When both biological elements, fish and macroinvertebrates were considered in the multiple regression model, a statistically significant relationship (R2 = 0.573, P \ 0.005, df = 3.16) was found only between macroinvertebrates and PC2 scores
3S
2
4A
3A 4S
8A 8S
2S
5S
PC2 (19.6%)
Samples
2A 6S
0
1S
5A
6A
10A 9A
Altitude TSS
10S 9S
NO2-N NH4-N PO4-P
1A
-2
CaCO3 Conductivity
-4
7A 7S
-6 -4
-2
0
2
4
6
PC1(32%) Fig. 3 Principal Component Analysis (PCA) plot of the first two PC axes on the transformed environmental data (A autumn S spring). The length of the vectors in this plot reflects the significance of each variable contribution to each axis. If the vector reaches the circle, then none of that variable’s coefficients differ from 0
(beta-weight = 0.799, P = 0.0004), while relationship with fish and PC1 was not significant (P [ 0.05, betaweights 0.371 and 0.220 respectively).
Discussion In the present study, we used biotic (fish and macroinvertebrates) and abiotic elements (hydromorphological, physicochemical), as well as five indices (HES, AHES, HESII, HMS, and QBR) and multivariate analysis to assess the impact of anthropogenic activities along a small Mediterranean Greek river (RM4 type), and evaluate its ecological quality as the WFD demands. Biological and environmental elements demonstrated a declining ecological status along the river’s course. Macroinvertebrate
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assemblages responded better to local stressors than fish reflecting changes in riparian habitat quality and/or water chemistry. Studies such as this, which combine different bio-indicators for assessing river ecological status, are scarce in European and more particularly, Mediterranean rivers (Iliopoulou-Georgoudaki and others 2003; Dama´sio and others 2007). Physicochemical parameters, such as TSS, NH4-N, and B.O.D.5 values exceeded the national suggested limits for the maintenance of Salmonidae (TSS B 25 mg/l, NH4 B 0.04 mg/l, B.O.D.5 B 3 mg/l) and Cyprinidae (TSS B 25 mg/l, NH4 B 0.4 mg/l, B.O.D.5 B 6 mg/l) species at downstream sites 9 and 10, demonstrating their impaired status. This was also evident by their position on the PCA plot (Fig. 3). Ammonium concentrations were also higher than the suggested limit for Salmonidae species maintenance at mainstream sites 2, 6, and 8 during spring, due mainly to locally untreated sewage effluents. Agricultural use of fertilisers and/or point sources of pollution (sewage and waste) may be responsible for higher concentrations of NH4-N and NO3-N in spring, a pattern that has been reported for other small-sized watercourses in mainland Greece (Lazaridou-Dimitriadou and others 2004). Despite the differences observed between the two sampling periods, the impairment of water physicochemistry along the river’s course was evident, since sites located close to springs (1, 3, 5, 7) exhibited better physicochemical quality compared to sites located on the main river course (2, 4, 6, 8, 9, 10), as observed elsewhere (Kotti and others 2005; Casas and others 2006). This pattern was also traced when the QBR index was considered, since riparian quality was excellent and/or good at the tributaries at sites located near springs and moderate in the main river reaches. Such a longitudinal degradation in riparian habitat quality has been attributed by several researchers to agricultural and urbanization activities (Tabachi and others 1998; Lovell and Sallivan 2006; Stone and others 2005; Del Tanago and De Jalon 2006; Degerman and others 2007), as seems to be the case of Tripotamos. Nonetheless, the HMS score indicated that the three sites (2, 5, and 7), located at the tributaries, had obviously been modified due to water abstraction. However, the HMS and QBR scores did not correlate to fish abundances, indicating that artificial modification and deterioration of riparian habitat quality, although evident, were not severe enough to influence fish assemblages. On the contrary, QBR scores correlated strongly to the relative abundances of pollution sensitive and tolerant macroinvertebrate families, as well as sensitive taxa richness, indicating the strong influence of riparian quality on macroinvertebrtate assemblages. Key differences in life-history characteristics of these two organism groups make macroinvertebrates more responsive to local-scale habitat conditions and fish more affected by
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larger scale impairment (Hering and others 2006; Johnson and others 2006; Infante and others 2009). This difference in both biota’s response was also supported by the results of multiple regression analysis. Only macroinvertebrate abundances were significantly correlated with PC2 scores, suggesting differences in the response of the studied biota to the environmental gradient. The significant differences observed between the relative abundance of Limnephilidae (Trichoptera, sensitive to pollution) and Tipulidae families (Diptera, tolerant to pollution) in early autumn could be attributed to the emergence of macroinvertebrate adults of certain species belonging to the above families (Pritchard 1983; Voshell and Reese 2002). Local environmental variables such as temperature (Wagner and Gathmann 1996) and the amount of available prey (Wagner and Gathmann 1996; Ivkovic and others 2007) or the emergence of some species (Wagner and Gathmann 1996) in autumn, may be responsible for the statistically higher Empidid abundance in spring. The CCA analysis indicated that TSS, hardness, and conductivity were the most significant factors explaining macroinvertebrate variance (Fig. 2). TSS was the variable best correlating to the first axis of CANOCO, which distinguished severely and moderately impacted mainstream sites (8, 9, 10) from the moderately impacted (2, 4, 6) ones located upstream and the sites in the tributaries (1, 3, 5, 7). Severely impacted sites (9, 10), were set apart at the end of the positive side of axis I, having the lowest dissolved oxygen concentration and the highest TSS, B.O.D.5, NO2N, and PO4-P concentrations. The importance of TSS in shaping the benthic macroinvertebrate community was evident in previous studies of the Aliakmon river system (Lazaridou-Dimitriadou and others 2000) and of other rivers of Northern Greece (Kampa and others 2000; Lazaridou-Dimitriadou 2002) and elsewhere (Roy and others 2003; Casas and others 2006). High altitude sites, with a better quality, were ordinated on the negative side of axis I whereas low land sites on its positive side, indicating a longitudinal pattern of the macroinvertebrate communities. Sensitive to pollution taxa (Rhyacophilidae, Hydropsychidae, Taeniopterygidae) characterized high altitude springsites (1, 3, 5) whereas moderately tolerant to pollution families (Elminthidae, Planariidae, Gammaridae, Sphaeridae etc.) high altitude sites located at the main river coarse (2, 4). Finally, tolerant to pollution taxa (Chironomidae, red Chironomidae, Tubificidae, Hygrobiidae, and Physidae) dominated low land mainstream sites (8, 9, 10) (Fig. 2a, b). Hardness and conductivity were the variables best correlating to the second CCA axis, which distinguished site 7 from the rest of the sites, due to its presenting the highest conductivity values recorded. Conductivity is generally referred to as an important environmental factor, influencing macroinvertebrate assemblages in Greek rivers
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(Iliopoulou-Georgoudaki and others 2003; LazaridouDimitriadou and others 2000; Skoulikidis and others 2009). Higher values of conductivity, hardness, and pH at minimally impacted site 7 could be attributed to its unique geology and/or to low discharge values that elevate the concentration of solutes. Longitudinal patterns of fish presence partitioned the river into two clear zones, the brown trout, Salmo trutta (headwaters) and the barbell, Barbus balcanicus (downstream). Fish were absent from two sites in the Salmo zone (1, 5), which exhibited good water quality (Table 3). This is consistent with other findings which demonstrate the absence of fish or the presence of very few in many streams, even with relatively good water quality, suggesting that fish community response is strongest at relatively low stressor concentrations (Freund and Petty 2007). Salmo trutta population was mainly present at two moderately impacted sites (2, 4) according to the HES (moderate water quality). Sites occupied by Salmo trutta population presented higher altitude, and generally low TSS and nutrients (Fig. 3). Barbus balcanicus, a species tolerant to moderate organic pollution (Economidis 2003), was mainly present at two sites, presenting excellent and good (site 7) or moderate (site 8) water quality. Fish were not captured in downstream sites (9 and 10) in either sampling periods. The bad/poor water quality of these sites, demonstrated by physicochemical parameters, macroinvertebrate assemblages, and HES (bad and poor water quality), seemed to be unfavourable for Barbus balcanicus. Fish elimination may occur when human disturbances are intense (VilaGispert and others 2002; Adams and others 2005). However, fish presence within a river sector is known to be strongly influenced by the dispersal of individuals among river networks within a drainage area (Fausch and others 2002). Thus, the location of a stream within a drainage network can be of crucial significance in determining local species richness (Freund 2004). The presence of few fish species in a river section makes it difficult to obtain a clear response to disturbance, and it is a limiting factor in the development of most metric indices based on fish assemblages (Ferreira and others 2007). Therefore, when fish are used in ecological quality assessment, assemblage-based metrics may have a limited capacity to detect stressors (Hering and others 2006). Species-based metrics, e.g. trout biomass or the proportion of juveniles, might show stronger responses to stressors (Hering and others 2006). The percentage of morphological anomalies is a metric used by the Index of Biotic Integrity (IBI) (Karr 1981). However, this metric is not included in the European Fish Index (Pont and others 2007), or in the fish index proposed by Economou and others (2007) for the assessment of the ecological status of Greek mountain streams. In our case, fish with morphological anomalies and pathological signs
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were observed at two of the six (33.3%) sites with fish presence. Moreover, the percentage of fish specimens with anomalies was found to be significant, since it was higher than the limit of 3% in reference sites in Oklahoma streams (Spence and others 1999). These kinds of pathological signs in fish are pollution-related (Moore and others 2005), as well as season-depended. Bowser and others (1988) demonstrated an inverse relationship between skin tumours and water temperature. This relationship could also explain the differences observed in our case at site 8 between spring, characterized by lower temperature, and autumn sampling. Furthermore, 16% of fish specimens caught at site 7S during spring had red spots (but no other pathological signs such as skin tumours, missing parts of the operculum and/or the caudal fin), while those sampled during autumn did not have any pathological signs. This confirmed not only the seasonal related presence of pathological signs in fish but it was also followed by the change in water quality detected by HES (7A: excellent water quality, 7S: good water quality). Lower environmental temperature in spring, evident at sites 7 and 8, may affect the immune response of fish in natural habitats and make them more susceptible to infection (Avtalion and Clem 1981). Salmo trutta individuals did not have any pathological signs although they were mainly present at sites with moderate water quality (2, 4). Since small streams and rivers in Greece, such as the Tripotamos river (2 species), support limited fish fauna (average fish richness per site: 2.5 species; Ferreira and others 2007), but diverse macroinvertebrate fauna, the latter may be a more robust indicator of environmental degradation, although metrics like external pathological anomalies (a quick and easy metric to be observed) could be included in further development of multi-biota metric. Ecological Quality Evaluation The HESII results indicated that sites near springs had good or excellent water quality, sites moderately impacted by organic pollution (agricultural run-off, untreated waste) had moderate water quality, and sites severely impacted (urban and industrial activities) had bad or poor water quality. HES, AHES, and HESII correlated strongly to a chemical degradation gradient (PC1 scores), which separated sites with good water quality located upstream near springs (1, 3, 5, 7) from downstream polluted ones (9, 10). A longitudinal degradation trend was evident by the strong correlation between site distance and HESII results. Agricultural activities in small catchment areas can cause moderate reduction of ecological potential, which further deteriorates in urban areas (Halasz and others 2007; Heatherly and others 2007). Taxa richness increased in site 9 in spring compared to autumn which correlates with
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moderately tolerant and pollution sensitive taxa. Physicochemical variables did not demonstrate improvement in water quality in spring in the way that benthic community structure did. Lower biotic indices and scores in autumn than in spring, at sites affected by seasonal industrial activities, were evident in the same river system (Aliakmon) (Lazaridou-Dimitriadou and others 2000). Implementations for Restoration Our results have shown the declining ecological status along a small Greek, RM4 type river, suggesting the need for management improvement as regards point and nonpoint sources of pollution and riparian habitat so that a good ecological status may be achieved by 2015, according to the WFD demands. Improvement of the efficiency of peach canning plants, appropriate refining of livestock wastewater treatment plants and sewage plants, as well as regular inspection by local competent authorities could enhance river water quality status by lowering nutrient concentration and TSS content. Small village sewage treatment systems and sewage pipe connection to the main drainage system could also improve water quality in moderately impacted sites located at the main river course. Consequent reduction in organic contaminant exposure could improve fish health (Moore and others 2005). Termination of agricultural activities within the optimum width of the riparian vegetation zone (Del Tanago and De Jalon 2006) could retain nutrients from agricultural lands, limit erosion, trap suspended particulates and reduce nonpoint water pollution in general (Correl 2005). Consequently, the above measures are expected to improve water and riparian quality and allow the lower river parts in particular to be re-occupied by fish and certain macroinvertebrate taxa.
Conclusions Our findings revealed a longitudinal degradation in ecological status. Macroinvertebrates related strongly to local stressors as chemical degradation and riparian quality impairment while fish did not. However, the observed dissimilarity in the way both biota respond to the environmental gradients could reflect scale-dependent differences (Infante and others 2009). Macroinvertebrates are known to respond to more local-scale stressors, due mainly to their sort life-history and their limited mobility, while fish are influenced by large-scale impairment, owing mainly to their capacity to move and avoid impacted areas (Hering and others 2006; Johnson and others 2006; Infante and others 2009). Nonetheless, this large-scale dependence in the response of fish assemblages and moreover, the
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concordance of macroinvertebrate and fish responses to environmental degradation did not clearly rise from our results. As Paavola and others (2006) and Infante and others (2009) showed, this concordance among different biota is stronger when several river basins are studied and weaker when a single watershed is considered, as in our case of Tripotamos river. Additionally, since our results were based on biota’s abundances, further inclusion of other metrics describing their trophic ecology, habitat selection (Infante and others 2009) as well as trout biomass, age distribution and/or percentage of pathological signs should be considered. Finally, we also support, as it has already been proposed (Hering and others 2006; Hughes and others 2009), the combined use of both macroinvertebrates and fish in biomonitoring programs, since they can provide a more robust assessment of local and regional habitat impairment. Our findings add to the existent knowledge on the way the selected biota respond to anthropogenic pressures and contribute to the development of a multi-biotic index, adequate for the ecological assessment of RM4 type rivers. Acknowledgments We wish to thank Drs A. Economou, R. Barbieri and S. Zogaris for their advice regarding fish sampling and Dr Y. Chatzinikolaou, Msc. X. Statiri, Msc. A. Patsia, Msc. E. Kalopesa, and Mrs. D. Sporela, senior clerk of the Fisheries Department of Imathia Prefecture, for their technical support. We would also like to thank the four unknown reviewers for their constructive comments. This study was mainly self-funded by the first author and by the scholarship program of Msc students of the Aristotle University of Thessaloniki.
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